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Proceedings Paper

Explicit solutions of one-dimensional total variation problem
Author(s): Artyom Makovetskii; Sergei Voronin; Vitaly Kober
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Paper Abstract

This work deals with denosing of a one-dimensional signal corrupted by additive white Gaussian noise. A common way to solve the problem is to utilize the total variation (TV) method. Basically, the TV regularization minimizes a functional consisting of the sum of fidelity and regularization terms. We derive explicit solutions of the one-dimensional TV regularization problem that help us to restore noisy signals with a direct, non-iterative algorithm. Computer simulation results are provided to illustrate the performance of the proposed algorithm for restoration of noisy signals.

Paper Details

Date Published: 22 September 2015
PDF: 8 pages
Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959926 (22 September 2015); doi: 10.1117/12.2187866
Show Author Affiliations
Artyom Makovetskii, Chelyabinsk State Univ. (Russian Federation)
Sergei Voronin, Chelyabinsk State Univ. (Russian Federation)
Vitaly Kober, Chelyabinsk State Univ. (Russian Federation)
Ctr. de Investigación Científica y de Educación Superior de Ensenada (Mexico)


Published in SPIE Proceedings Vol. 9599:
Applications of Digital Image Processing XXXVIII
Andrew G. Tescher, Editor(s)

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